IS-95 CDMA, or commonly called CDMA, is a digital cellular radio system that has been in use in over 35 countries in the world. In 1998, over 23 million CDMA phones were in use and the prediction is that by the year 2002, there will be over 106 million CDMA phones. A CDMA network can provide for mobile voice communication as well as many new advanced services like mobile fax and text messaging.
As is well known in the art, CDMA is a form of spread spectrum communication, which transmits a radio signal over a radio channel that is much wider than necessary to transmit the original information signal (typically voice). Since the signal is spread over a very wide bandwidth, interference from other users within that bandwidth can be made minimal. This allows multiple users to share the radio channel at the same time by assigning a unique code sequence to each mobile radio. For more background regarding CDMA or CDMA IS-95, reference can be made to a book, entitled CDMA IS-95 FOR CELLULAR AND PCS, by Lawrence Hart, McGraw-Hill, 1999. A U.S. Pat. No. 4,901,307, issued Feb. 13, 1990, entitled “Spread Spectrum Multiple Access Communication System Using Satellite or Terrestrial Repeaters” also discloses the use of CDMA techniques in a multiple access communication system. Both of the above publications are incorporated herein by reference.
Despite progress made in CDMA to minimize interference, there is still the undesirable interference from multiple access (“MAI”). As can be appreciated by those skilled in the art, MAI is caused by non-zero cross-correlation between codes used to separate multiple users at the same time and in the same frequency band. In other words, the signal received by a CDMA receiver, whether it is at the base station or at the user's handset, represents the sum of all users' signals. Once received, the receiver uses the desired user's code to correlate and filter out the desired user's signal.
In the conventional design for CDMA base station receivers, MAI is treated as a Gaussian noise without any mitigation or cancellation. The receiver matches to the code of the desired user and decodes its information.
One conventional MAI cancellation technique is what is known as the Multistage Parallel Interference Cancellor (“MPIC”). The MPIC for base stations was first proposed in 1990 by Varanasi and Aazhang, “Multi-Stage Detection in Asynchronous Code-Division Multiple-Access Communications,” IEEE Transactions on Communications, vol. 38, pp. 509-519, April 1990, the disclosure of which is incorporated herein by reference. The MPIC technique generally works in the following stages. First, each user's signal is demodulated as in the conventional receiver, but the estimated bits are not final. Second, these estimated bits are used to regenerate the spread signal, which is MAI with respect to the desired signal. Third, the regenerated MAI is subtracted from the received signal for each user. Fourth, repeat the first step until the required performance is met.
FIG. 1 shows a simplified conventional MPIC for a base station receiver. For the sake of illustration, only 2 users' bits, a1 and a2, are discussed. At box 105, the received signal Y (100) is correlated with PN1 to generate an estimated bit for a1 (104). This estimated bit is used to generate known interference of a1PN1 (107) with respect to another user bit a2. This signal is further spreaded and weighted by its respective channel to replicate the signal received by the antenna (123, 124). The received signal Y is then subtracted by the known interference a1PN1, which has been spreaded and weighted, to generate a2PN2, which is then correlated with PN2 to derive the user bit a2. Similar steps are taken to derive a1. At this time, both a1 and a2 are considered a “first stage” value, since this MPIC process can be extended multiple times to fine-tune the value, provided the system processing resources are available.
Reference is now to FIG. 1(b), where another simplified diagram illustrating the conventional enhanced MPIC with multiple fingers used by the receivers. The receiver uses an antenna 10 and RF/ADC 12 to convert the received composite signals to composite baseband digital signals. The composite baseband signals are then split into multiple fingers 14, where the number of fingers equals the number of multipaths, for despreading 16, i.e. correlating the composite baseband signals with the PN of a desired user. The despreading generates a single user's multipath signal, which unfortunately still contains MAI. Each finger is then applied to maximal ratio combining (“MRC”) 18, weighted by the complex conjugate of the channel gain estimate for each multipath to increase the SNR the same number of times as the number of fingers. The output of the MRC 18 will be used to estimate the present stage information bits.
As can be appreciated by those skilled in the art, the conventional enhanced MPIC technique has the following advantages: low delay compared to serial cancellation, low complexity, since its complexity grows only linearly with the number of users, and incremental operation and performance. This MPIC can also achieve better performance than that of a simple MPIC due to lower initial BER from MRC.
The conventional enhanced MPIC, however, still has its drawback. At low signal-to-noise ratio (“SNR”) and limited multipath environment, better performance (than matched-filter) cannot be guaranteed, since the estimated bits tend to be wrong. Such error causes bad MAI generation for cancellation.
Aiming at decreasing the bit-error rate (“BER”) to increase the reliability of the MAI regeneration, it has been proposed to use smart antennas to enhance the multipath intensity profile (“MIP”) and to achieve space diversity SNR gain, which ensures a lower BER on every cancellation stage. With the help of space processing, the number of iterations can be reduced significantly for a specified BER.
However, the underlying assumption for using antennas to increase diversity gain has been that the interference surrounding the desired user is uncorrelated among the antenna inputs. Such assumption is true when there are more than five users of equal power, which is a typical scenario of a 2G wireless system where voice users are dominating. But, this assumption tends to fail in the cases where there are fewer than five users around the desired user, where all users are high-speed data users, or where there is one or two high speed data users with other voice users around the desired user.
As can be appreciated by those skilled in the art, the above two cases can be typical scenario in a third generation system (“3G”) such as the CDMA-2000 with radio configuration (“RC”) higher than 3, where high-speed data users trade many voice users. The assumption tends to fail in first case in due to the fact that the interference will not appear like white Gaussian noise if only a small number of users. The assumption fails in the second case is due to the few high-speed data users carrying much higher power and their effects on the different antennas being correlated for the same reason that CLT cannot apply to make it Gaussian noise. Also, when the high-speed data users are active, the number of voice users will be reduced based on the rule of trading the Walsh codes for the data rate, thus making the voice users appear less like Gaussian.
Therefore, antenna diversity gain is not achievable when the interference are correlated as in the cases described in a 3G system. However, antenna process can be performed to mitigate the correlated interference.
Also, it is desirable to cancel the correlated interference before it gets into time process, because MRC is not optimal with correlated interference among fingers.